Quadrat Analysis of Urban Dispersion: 4. Spatial Sampling

1972 ◽  
Vol 4 (3) ◽  
pp. 331-345 ◽  
Author(s):  
A Rogers ◽  
R Raquillet
Keyword(s):  
Spatial Dispersion ◽  
Spatial Sampling ◽  
Urban Dispersion ◽  
Probability Sampling ◽  
Sampling Schemes ◽  
Quadrat Analysis

This paper is the concluding part of a four-part essay on quadrat analysis. It shows how quadrat analysis of spatial dispersion may be linked with Jessen's (1970) method of probability sampling with marginal constraints to produce more efficient spatial sampling schemes.

Quadrat Analysis of Urban Dispersion: 3. Bivariate Modelst

1971 ◽  
Vol 3 (4) ◽  
pp. 433-450 ◽  
Author(s):  
A Rogers ◽  
J Martin
Keyword(s):  
Empirical Study ◽  
Urban Areas ◽  
Spatial Dispersion ◽  
Spatial Clustering ◽  
Urban Dispersion ◽  
Food Stores ◽  
Residential Population ◽  
Previous Discussion ◽  
Bivariate Models ◽  
Quadrat Analysis

This paper is a continuation of an earlier two-part essay on quadrat analysis. It extends the previous discussion by introducing bivariate models of spatial dispersion to analyze statistically the correlated spatial clustering of food stores and population in urban areas. The data used for empirical study are the spatial patterns of food stores and residential population in Ljubljana, Yugoslavia.

Optimization of spatial sampling schemes for maize acreage estimation

2015 ◽  
Vol 9 (1) ◽  
pp. 097092
Author(s):  
Di Wang ◽  
Qingbo Zhou ◽  
Zhongxin Chen ◽  
Jia Liu
Keyword(s):  
Spatial Sampling ◽  
Sampling Schemes ◽  
Acreage Estimation

Quadrat Analysis of Wildland Fuel Spatial Variability

1992 ◽  
Vol 2 (4) ◽  
pp. 145 ◽  
Author(s):  
KD Kalabokidis ◽  
PN Omi
Keyword(s):  
Pinus Contorta ◽  
Wildland Fire ◽  
Small Sample ◽  
Sample Sizes ◽  
Optimum Range ◽  
Sampling Schemes ◽  
Big Sagebrush ◽  
Small Sample Sizes ◽  
Wyoming Big Sagebrush ◽  
Quadrat Analysis

Quadrat analysis of two fuel properties (loading and depth) was used to assess the relation between variation and sample plot size. By this method, an optimum range of spatial resolutions was established for sampling Artemisia tridentata subsp. wyomingensis (Wyoming big sagebrush) and Pinus contorta (lodgepole pine) fuel types in Colorado. Results of the analysis demonstrated that quadrats provide homogeneous strata and precise measures of central tendency on both fuelbeds studied. Findings indicated that field inventories in which A. tridentata is viewed as a fire fuel could use sample spacings up to 60 m (i.e., reasonably small sample sizes). The optimum range of resolution for the P. contorta fuel type was down to 20-30 m so that larger sample sizes are required. Quadrat analysis shed light on more precise fuel sampling schemes by accounting for the microsite variation of fuel characteristics. Thus, analogous studies can reveal further the semi-stochastic phenomena that govern wildland fire behaviour and effects.

A comparative analysis of different spatial sampling schemes: Modelling of SSRB data

2008 ◽  
Vol 29 (6) ◽  
pp. 1635-1647 ◽  
Author(s):  
F. Martínez ◽  
J. Mateu ◽  
F. Montes ◽  
A. Bodas‐Salcedo** ◽  
E. López‐Baeza
Keyword(s):  
Comparative Analysis ◽  
Spatial Sampling ◽  
Sampling Schemes

Optimal spatial sampling schemes for environmental surveys

2004 ◽  
Vol 11 (4) ◽  
pp. 397-414 ◽  
Author(s):  
Simone Di Zio ◽  
Lara Fontanella ◽  
Luigi Ippoliti
Keyword(s):  
Spatial Sampling ◽  
Sampling Schemes ◽  
Environmental Surveys

Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops

2016 ◽  
Vol 80 ◽  
pp. 100-112 ◽  
Author(s):  
Gang Zhao ◽  
Holger Hoffmann ◽  
Jagadeesh Yeluripati ◽  
Specka Xenia ◽  
Claas Nendel ◽  
...  
Keyword(s):  
Spatial Sampling ◽  
Sampling Schemes

Quadrat Analysis of Urban Dispersion: 2. Case Studies of Urban Retail Systems

1969 ◽  
Vol 1 (2) ◽  
pp. 155-171 ◽  
Author(s):  
A. Rogers
Keyword(s):  
Spatial Structure ◽  
Case Studies ◽  
San Francisco ◽  
Empirical Data ◽  
Urban Areas ◽  
Urban Dispersion ◽  
Generalized Distributions ◽  
Empirical Tests ◽  
Quadrat Analysis

This is the second part of a two part paper; the first part reviewed the methodology of quadrat analysis and in this part, two case studies are presented. A brief introduction outlines the spatial structure of retailing in urban areas and it is then demonstrated how compound and generalized distributions offer a variety of models that can be fitted to empirical data about retail spatial structure. The empirical tests use data from Ljubljana, Yugoslavia and San Francisco, California. Conclusions are drawn which relate to the description, analysis and sampling of intra-urban retail spatial dispersions.

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